... Aris, solo founder who got fed up with clunky passwords and 2FA fatigue after years of building web apps. So I created QRAuth.io , an open-source passwordless auth system where you simply scan an animated living QR code with your phone, tap once with biometrics or passkey, and you re instantly logged in. No apps, no typing, no copy-paste, it works on any website, kiosk, menu, or even physical products, and it s cryptographically signed so screenshots are useless ...

... Quick story that pushed me to build PriceForge : Three weeks ago, I was in final stage of a $50K deal. Sales call went great. Then the pricing objection hit: Prospect: "Your competitor just dropped their Pro tier to $79/mo with unlimited workspaces." Me: frantically opening competitor

... what's missing, right - because we don7t already have enough to do...? I genuinely want to know if I'm wrong, but I know of nothing but MentionFox.com that actually trains the LLMs to actively promote our products over competitors' offerings. Do you? Please do share in the comments. Yes, we are prepared to prove it. MentionFox offers the same to you: sign up with work email and give us three or more competitors

... reading Nika's thread here about free vs paid features. Really made me think. Link: https://www.producthunt.com/p/ge... ( shout-out to @busmark_w_nika ! ) She talks about giving generalized advice for free, but charging for specific, tailored help. That's a good framework. But most product owners figure this out after they build, not before. That's backwards. Your free tier should be designed before you write a single line of code. Because it's not just a marketing tool ... ... everything in the free tier. Now nobody upgrades. You have users but no revenue. Giving away too little. The free tier is useless. People sign up, see nothing, and leave. You never had a chance to convert them. Copying competitors

... this guide isn't just a quick summary. We're going to go deep. We'll explain exactly what Snaply is, how it works, why privacy matters so much for dictation tools, how it stacks up against every major alternative, who it's best for, and how to get the most out of it. Whether you're a solo professional, part of a team, or evaluating dictation software for an enterprise deployment, this is the most complete breakdown ... ... find. Table of Contents Why AI Dictation Matters in 2026 What Makes a Truly Great Dictation App What Is Snaply? Snaply's Core Features: In Depth Why Privacy Is Non-Negotiable for Dictation Snaply vs

... built a tool that watches Reddit for competitor mentions and texts you here's why Last year I kept seeing posts like "looking for a Notion alternative

... months ago, we ran an experiment with our own data. At Rankfender, we tracked 5 of our own competitors across 8 AI systems. We log their share of voice, citation velocity, content gaps, platform variance. Months of raw numbers sitting in a dashboard. I pulled 6 months of data and fed it into Claude. One question: "Based on this, who is most likely to overtake us in the next 6 months? Show your work. Use the data. Don't summarize ... ... Give me the numbers." The answer changed how I think about competition. The dataset: 5 competitors

... Last month, I did something that felt slightly insane. I took our product description, fed it into ChatGPT, and asked it to build a competitor. Not a parody. A real competitor

... just exposure, but the degree to which AI treats your brand as a credible source . Share of Voice (SOV): Represents your brand s voice share within AI narratives the probability that AI mentions your brand rather than a competitor when answering a topic-related question. Sentiment: Captures the emotional tone of AI mentions positive, neutral, or negative showing how AI portrays your brand. Together, these four metrics answer the two most fundamental GEO questions: How frequently does AI mention ... ... brand? and In what tone and context is the brand represented? 1.2 Trends and Competitor

... clearly dropped. But the more I use these tools, the more it feels like speed isn t the limiting factor anymore. The real constraint seems to be taste. what do you choose to build? what do you keep vs discard? what actually feels right vs

... Maybe more. Here's the painful truth: Your site is translated. Your AI visibility isn't. When a German user asks ChatGPT in German about your category, you're invisible. When a French prospect searches Perplexity in French, your competitor shows up. Translation AI visibility. And it's costing you. The Data We tracked 200 SaaS companies with multilingual sites at Rankfender. Market % Visible in Local AI Answers US (English) 64% UK (English) 58% Germany (German) 22% France (French ... ... Founder: B2B SaaS, 8M ARR "We spent 40k translating our site into German and French. Beautiful work. Native speakers. Perfect messaging. Six months later, we checked German AI answers about our category. We weren't there. Not once. Our competitor

... project management tool for remote design teams. Here's exactly how we work." Feature lists Problem-solution paragraphs Vague benefits Specific outcomes Lesson #2: AI Loves Comparisons Even If You Lose This one hurt. I avoided mentioning competitors. Why give them free airtime? Wrong move. Every AI answer about your category includes comparisons. Always. If you don't provide the comparison, AI finds someone who does and that someone might be your competitor

... answer about your category includes comparisons. Always. When someone asks "best CRM for agencies," AI doesn't list one tool. It lists 3-5. And it compares them. The data: Content Type Citation Rate Pages with comparison tables +470% vs. average Pages that mention competitors

... community I want to share something I've been building - Upvotics, a competitive intelligence platform for founders, marketers, and product teams who are tired of finding out what their competitors changed way too late. The problem I kept running into was simple. A competitor

... many found they were invisible. But here's what scared me more: Of those who WERE visible, 43% had incorrect information in AI answers. Not "suboptimal." Not "could be better." Wrong. Outdated pricing. Missing features. Wrong founder bios. Competitors credited for your work. And the average error sticks around for 4 6 months . Today, I'm sharing the full dataset: 1,000+ SaaS products, 75,000+ AI answers, and the hard truth about what's being said about you when ... ... analyzed 50 brands that discovered errors and tracked the impact. Error Type Average Revenue Impact Pricing error (higher than actual) 47,000 Pricing error (lower than actual) 23,000 (leakage) Missing critical feature 38,000 Wrong positioning (enterprise vs

... Rankfender , we've identified clear patterns. Certain content types get cited 3x more often than others. Here are the 7 content types that win AI citations with real examples you can steal. First, the data: Content Type Citation Rate (vs. average) Best For Comparison pages 3.2x higher "X vs

... Minute Audit Step 1: Keyword Selection (5 minutes) Choose 20 keywords to audit: 10 branded keywords: Your company name Your product names Your founder/CEO name Your flagship features 10 non-branded keywords: "[Your category] best tools" "[Your category] alternatives" "How to [solve problem you solve]" "[Your category] vs

... Average monthly retainer for AI visibility audits 1,200 2,500 Average monthly retainer for ongoing AI visibility + content 2,500 5,000 First-mover advantage is real. The agencies offering this now are locking in clients before competitors even know the category exists. Service Model #1: The One-Time AI Visibility Audit What it is: A comprehensive audit showing where the client appears (or doesn't) across ChatGPT, Google SGE, Perplexity, and Gemini. Deliverables: 20 50 keywords analyzed Screenshots ... ... actual AI answers Competitor

... schema 71% 19% Cite data sources 68% 27% Part 3: What content wins AI citations? This is the question everyone asks. Here's the data: Top 5 content types by citation rate: Comparison pages (X vs Y) 3.2x average Structured FAQs 2.8x average Data-driven articles (with stats, tables, studies) 2.4x average "How to" guides (step-by-step) 1.9x average Original research 1.7x average What performs poorly: Short opinion pieces Thin content (<500 words ... ... great for blue links. But none of them show you how you appear in AI answers. Here's what we track: Actual AI-generated answers mentioning your brand Citation rates across ChatGPT, Google SGE, Perplexity, Gemini Share of voice vs

... answer first. If they find it immediately, they cite it. The structure makes extraction easy. Step 2: The Comparison Page Template Comparison pages drove 40% of our citation growth. Here's our exact template: Title: [Brand X] vs [Brand Y]: Which is better for [use case]? Quick verdict (100 words) Who wins and why One sentence summary Feature comparison table Feature Brand X Brand Y Feature A Feature B Feature C Price XX YY Detailed breakdown (by feature) How each ... ... margin of error. Result: This block was cited verbatim by Perplexity within two weeks. Step 5: The 90-Day Update Cycle We analyzed citation decay across 500 pages. The drop-off is steep: Months Since Update Citations (vs

... connects directly to GSC and runs real-time analysis across 50+ SEO aspects: Top Page and Query Performance Top Mover Delta Analysis Growth and Decay Analysis Performance Trends Rank Disparity Analysis CTR Uplift Analysis Impression and CTR Segmentation Brand vs. Non-Brand Performance Cannibalization Analysis Topical Cluster Performance Device Parity Analysis Device Distribution Country Performance Long Tail Performance Trust and Authority Analysis Then it doesn't just report it. It moves from Performance Opportunity Analyze Fix Apply. Automatically. Comes with ... ... audits. Then: AI Brand Visibility Brand Analysis Prompt Run Prompt Tracking Competition Tracking Citation Tracking Monitored across Gemini, ChatGPT, Claude, Perplexity, Grok, and LLaMA. It surfaces missing semantic anchors, authority gaps, structural issues, knowledge reinforcement weaknesses, and citation loss vs

... plays a significant role in how products appear in Google search results. What surprised us was that AI assistants like ChatGPT were rarely citing Product Hunt in product recommendations. AI assistants such as ChatGPT and Gemini rely on reviews, alternative lists, and structured product information gathered across the web. Product Hunt is strong across all three. In theory, this should make Product Hunt a natural source for AI-driven product recommendations and comparisons. In practice, it was not happening ... ... many tools which systematically run prompts against several AI models daily, and measure visibility of a product within prompts. We're using a new tool called @Gauge . We chose because a) their citation tracking is more useful than the alternatives

... weeks and honestly I m really happy with it, as long as it stays in copilot mode (I review everything before it ships). I ve leaned on it heavily for a new side project I m building ( BenchCanvas ): market + competitor research, branding notes, SEO ideas, PRDs, and even markdown instruction docs to run in Cursor. It s also been great as a second pair of eyes on the landing design and copy. So for me the trust line ... ... reliability Comment from Nika(@busmark_w_nika): @georgios_sarantitis_  IMO, vibecoding has meaning only for those, who are willing to understand the code (so at least understanding coding/programming itself). and not blindly copy paste. Comment from Dedy Ariansyah

... from anywhere. Yet when it comes to real estate, one of the biggest financial decisions of our lives, we're still stuck with processes that haven't evolved in decades. I've been trying to relocate from Indiana to Arizona since last summer. The traditional path? Pay 6% commission (~$24,000 on my home), wait 3-6 months for a buyer, then compete in a hot market on the other side. It felt broken. Here's the thing, I bought ... ... terms, handled the paperwork. It wasn't easy, but it proved to me that regular people CAN represent themselves if they have the right tools and information. So I kept thinking: what if there's someone in Arizona

... sparked an interesting thought experiment: how likely is it that we ll see AGI (AI that thinks and learns like a human) within the next five years? The report highlights a fascinating divergence: the view from money vs. the view from science. Money : the probability inferred from trillions poured into data centers, Nvidia chips, and servers. Investors seem to be betting that AGI is inevitable. Science : the probability inferred from research papers and AI development models. Experts are far more ... ... might be ahead of reality. Expect volatility, overpromised outcomes, and valuable lessons along the way. Meanwhile, AI continues reshaping work, attention, and human behavior. I d love to hear the community s perspective: Are you seeing this money vs